Modeling of the energy requirements of a non-row sensitive corn header for a pull-type forage harvester

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Date

2003-12-16

Author

Nieuwenhof, Philippe

Type

Thesis

Degree Level

Masters

Abstract

With the constant diversification of cropping systems and the constant increase in farm
size, new trends are observed for agricultural machinery. The increase in size of the
machinery and the increasing number of contractors has opened the market to selfpropelled
forage harvesters equipped with headers that can harvest row crops in any
direction, at any spacing. High-capacity pull-type forage harvesters are also in demand
but no commercial model offers non-row sensitive corn headers. The objectives of this
research were to collect data and develop models of specific energy requirements for a
prototype non-row sensitive corn header. The ability to better understand the processes
involved during the harvesting and the modeling of these allowed the formulation of
recommendations to reduce the loads on the harvester and propelling tractor.
Three sets of experiments were performed. The first experiment consisted of measuring
specific energy requirements of a non-row sensitive header, in field conditions, and to
compare them with a conventional header. The prototype tested was found to require
approximately twice the power than a conventional header of the same width, mostly
due to high no-load power. Some properties of corn stalk required for the modeling of
the energy needs, that were not available in literature, were measured in the laboratory.
Those include the cutting energy with a specific knife configuration used on the
prototype header and the crushing resistance of corn stalk. Two knife designs were
compared for required cutting energy and found not to be significantly different with
values of 0.054 J/mm2 of stalk cross-section area and 0.063 J/mm2. An average
crushing resistance of 6.5 N per percent of relative deformation was measured.
Three mathematical models were developed and validated with experimental data to
predict and understand the specific energy needs of the non-row sensitive header. An
analytical model was developed based on the analysis of the processes involved in the
harvesting. A regression model was developed based on throughput and header speed
and a general model suggested in literature was also validated with the data. All three
models were fitted with coefficient of correlation between 0.88 to 0.90.